Arbeitspapier
Flexible and robust modelling of volatility comovements: a comparison of two multifractal models
Long memory (long-term dependence) of volatility counts as one of the ubiquitous stylized facts of financial data. Inspired by the long memory property, multifractal processes have recently been introduced as a new tool for modeling financial time series. In this paper, we propose a parsimonious version of a bivariate multifractal model and estimate its parameters via both maximum likelihood and simulation based inference approaches. In order to explore its practical performance, we apply the model for computing value-at-risk and expected shortfall statistics for various portfolios and compare the results with those from an alternative bivariate multifractal model proposed by Calvet et al. (2006) and the bivariate CC-GARCH of Bollerslev (1990). As it turns out, the multifractal models provide much more reliable results than CC-GARCH, and our new model compares well with the one of Calvet et al. although it has an even smaller number of parameters.
- Sprache
-
Englisch
- Erschienen in
-
Series: Kiel Working Paper ; No. 1594
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Estimation: General
International Financial Markets
- Thema
-
Long memory
multifractal models
simulation based inference
value-at-risk
expected shortfall
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Liu, Ruipeng
Lux, Thomas
- Ereignis
-
Veröffentlichung
- (wer)
-
Kiel Institute for the World Economy (IfW)
- (wo)
-
Kiel
- (wann)
-
2010
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
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Objekttyp
- Arbeitspapier
Beteiligte
- Liu, Ruipeng
- Lux, Thomas
- Kiel Institute for the World Economy (IfW)
Entstanden
- 2010
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